How technology can make procurement more intelligent

Posted on
11/28/2017

By Scott Dewicki, Principal Customer Success Manager, Amazon Business

According to many observers, emerging technologies such as artificial intelligence (AI) could transform the business world. Business leaders are evaluating these areas in hopes of positioning their organizations to benefit through increased efficiency, reduced costs, and faster innovation. This new technology and “intelligence” have the potential to enhance procurement to be a better partner to the business and deliver even greater value to end customers.

Freeing people to do what they do best

One way that technology is making procurement more intelligent is by reducing the amount of time people spend on mundane tasks, using automation to free them for more strategic work. Automation is already present in procurement today, usually in the form of robotic process automation (RPA). RPA uses technology to make repeatable processes faster. Today’s purchasing technology already does this, with automated workflows, digital search capabilities and electronic procure-to-pay processes.

While these tools create efficiency and reduce error, they are just the first step: they are not truly intelligent. They work only for processes that are predictable and repetitive. They are not predictive, and they don’t provide people with recommendations about actions to take. However, technology is progressing to a point where it can make decisions like a human.

From descriptive to prescriptive

Moving from basic automation to intelligent procurement begins with capturing and understanding data in new, more in-depth ways. Today, most procurement analytics are purely descriptive. For example, they can tell you how much a department has spent in a month, which suppliers are meeting performance targets and past trends in materials prices.

As analytics develop, predictive models will become the norm. By analyzing data for hidden patterns using techniques such as machine learning, procurement could identify which departments are likely to overspend next month, which suppliers may be likely to face challenges next year and where materials prices are headed over the longer term. In the future, this information could drive procurement strategy, such as which suppliers to choose.

Digital agents: surfacing intelligent insights

The next step in intelligent procurement could be the use of digital agents such as chat bots to proactively deliver recommendations to procurement professionals. These agents could augment the experience and knowledge of buyers, empowering them to act on big data insights without having to become data scientists themselves. Using artificial intelligence, these technologies could learn when the best time is to engage with users and what actions drive the best outcomes. For example, if the machine learning model identifies a potential

How to position procurement for success

Intelligent procurement could help professionals create differentiated supply chain outcomes. For example, organizations can operate on a total-cost-to-serve model that is focused on meeting a wide range of customer needs. Algorithms can teach the supply chain how best to manage a broad network of suppliers to deliver various outcomes in a flexible way.

The ability to capture and analyze data are increasingly critical to maintaining a competitive advantage. As organizations evaluate solutions to support digital transformation, they should consider whether those solutions will provide the levels of detail and access they need to take advantage of emerging capabilities.

Additionally, departments should evaluate relevant skills when sourcing future talent. The ability to understand and embrace new technologies will likely be beneficial.

Scott joined Amazon Business as a Principal Customer Advisor in June 2017. With more than 25 years of product development and supply chain management experience, Scott has successfully led business initiatives spanning supply chain planning, inventory management, procurement and commodity management.